I build production REST APIs, event-driven backends, and LLM-powered features — and I document the journey so others can level up too. This profile doubles as a personalized Open Source Playbook.
A curated path of 100+ organizations & repos matched to my stack — backend, distributed systems, and AI tooling.
| Domain | Where I Contribute / Want To |
|---|---|
| Backend / APIs | nodejs, expressjs, fastapi, spring-projects |
| Messaging & Streaming | apache/kafka, rabbitmq, redis |
| Cloud & DevOps | kubernetes, docker, grafana, prometheus |
| GenAI / LLM | langchain, openai-cookbook, anthropics, embeddings tooling |
| Databases | mongodb, postgres, mysql, redis |
I track contributions like an engineering sprint:
- Scope — pick
good-first-issue/help-wantedaligned to my stack. - Reproduce — build a minimal harness before touching code.
- Fix + RCA — root-cause the bug, not just the symptom.
- Document — leave the issue clearer than I found it.
- APIs at scale — 100+ production REST endpoints across auth, payments, real-time data & LLM features.
- Security — JWT, OAuth 2.0, RBAC, rate limiting, token lifecycle management.
- GenAI — OpenAI / Anthropic / Gemini APIs, prompt engineering, embeddings, LLM integration.
- Performance — Redis caching (~60% latency cuts), code splitting, memoization.
- Event-driven workflows with Kafka / RabbitMQ / SQS to decouple sync paths.
- Containerized services on Docker + Kubernetes for zero-downtime rollouts & autoscaling.
- Full observability via Datadog · Grafana · Prometheus · CloudWatch (~50% lower MTTD).
Always iterating on how I present work — clean repos, meaningful READMEs, measurable impact statements over vanity metrics.
I write up what I learn — RCAs, system design breakdowns, and "what → why → tradeoff" deep-dives on Medium.
📫 Reach me at mdshahansha44411@gmail.com
Thanks for stopping by — let's build something open. 🤝